Senior AI-Driven Cloud FinOps Engineer

Jobs Paloaltonetworks; United States; On-site; USD 145,000 - 236,000; Full time

Job summary

Palo Alto Networks is seeking an AI‑Native Cloud FinOps Engineer to build intelligent pipelines and autonomous optimization for cloud spend across AWS, Azure, and GCP. You will shift to AI‑driven, self‑optimizing architectures, focusing on AI/ML compute infra and multi‑cloud cost control.

You will bridge deep systems engineering with ML, creating closed‑loop automation and telemetry platforms to detect waste and save costs. This role requires onsite Bay Area presence and strong FinOps expertise.

Qualifications

• 8+ years of experience in Software/Cloud Engineering or related fields.
• 2+ years building software tools or AI/ML integrations for cloud resource management.
• Strong Python, ReAct, and TypeScript/Node.js foundations.
• Experience interfacing with LLM APIs, vector databases, and agent frameworks.
• Deep understanding of AI/ML cost drivers and FinOps principles.
• Hands-on experience with AWS, GCP, and Azure FinOps APIs.
• Proficiency with Terraform and Pulumi for IaC; CI/CD tooling.
• Must be local to Bay Area and onsite.

Responsibilities

• Engineer autonomous systems to inspect, govern, and optimize high‑cost AI/ML workloads.
• Manage GPU cluster provisioning, model batching, and unit economics tracking.
• Develop closed‑loop software that converts optimizations into realized savings across clouds.
• Build IaC pipelines with Terraform and Pulumi with real‑time cost checks.
• Train and deploy ML models to analyze real‑time usage and detect spend anomalies.
• Advance FinOps maturity by building telemetry platforms to measure unit economics.
• Design internal AI agents to analyze infra state and submit pre‑validated PRs.

Skills

Python

ReAct

TypeScript/Node.js

LLM APIs

FinOps concepts

CI/CD

Tools

Terraform

Pulumi

Kubernetes

Kubecost/OpenCost

Job description

Palo Alto Networks is seeking an AI‑Native Cloud FinOps Engineer to build intelligent pipelines and autonomous optimization for cloud spend across AWS, Azure, and GCP. You will shift to AI‑driven, self‑optimizing architectures, focusing on AI/ML compute infra and multi‑cloud cost control.

You will bridge deep systems engineering with ML, creating closed‑loop automation and telemetry platforms to detect waste and save costs. This role requires onsite Bay Area presence and strong FinOps expertise.